Explore Your Edge AI Opportunity
Innovative capabilities at the edge, facilitated by new advancements in performance and efficiency, are poised to bring together the physical and digital worlds. Among the most promising is edge AI, which extends artificial intelligence out from the data center to the point where data is created to deliver real-time insights and make an even greater impact on real-world outcomes. In combination with cloud and data center resources, edge AI unlocks a complete end-to-end AI platform for your business, with enhanced support for real-time insights, automation, agility, and other game-changing capabilities.
Like many businesses across the globe, your organization is likely already assessing the potential of edge AI for your business and exploring how it can impact your operations. You’ve likely seen examples of how early adopters are already achieving amazing things through innovative AI-powered solutions and wondering how you can do the same.
In today’s business environment, quickly realizing value and staying ahead of your competitors through edge AI is an imperative that remains top of mind across industries. To help simplify and accelerate your journey to edge AI success, we’ve built a guide to the challenges you need to prepare for and the various best practices, resources, and technologies that can help you overcome them.
Let’s start by examining the most common hurdles that your business may encounter as you pursue edge AI capabilities.
Get Started with Edge AI
Edge AI and its business use cases are a complex and multifaceted topic. As a result, your organization will likely want to tackle AI enablement in phases. While the most-advanced and wide-spanning use cases will require a sophisticated stack of edge-to-cloud technologies, getting started with edge AI can be easier than you think.
As you begin exploring edge AI possibilities, keep in mind that your Intel-powered edge environments are likely ready to get started with AI today. Existing edge compute resources, like POS systems in your stores, industrial PCs, or local servers in healthcare offices, can support many AI workloads, including computer vision.
Since these resources are built on Intel, they also help promote interoperability between all of your AI environments, creating a unified fabric from edge to cloud. Our experience—powering the world’s clouds, networks, and enterprises with a common platform; years of work solving for critical operational and IT divides; deep work in open standards bodies; and over a decade of driving foundational networking and AI technology shifts—gives us rare insight on how to help your organization achieve unification and standardization across your heterogeneous infrastructure.
Whether you’re training models in the cloud, fine-tuning them, or deploying them at the edge, Intel offers a robust hardware portfolio that can help right-size your investment and support your performance requirements. Our range of AI processors supports the entire AI pipeline—from massively complex model training to simpler AI needs, including incorporating AI in end user devices. Integrated Intel® Accelerator Engines in Intel® Xeon® Scalable processors can help you power many advanced edge AI workloads without specialized hardware. And our lineup of GPU solutions can help power your most demanding workloads in the data center, at the edge, or in end user devices.
Select Your Adoption Approach
Organizations looking to extend AI applications to the edge generally fall into three categories: those looking to purchase a purpose-built AI solution or application, those looking to build their own AI application, and those looking to achieve their AI goals through some combination of those two approaches.
Regardless of the approach your organization wants to take, Intel has resources, technologies, and ecosystem partners that can help you achieve your goal. We’ve invested in translating our expertise into consumable offerings that help simplify your efforts to bring AI to the edge and connect seamlessly to your cloud and data center environments. Our capabilities extend across the entire spectrum of AI needs—from training to deployment and from relatively simple and easy-to-deploy applications to complex workloads.
From edge to cloud, you can rely on our underpinning technology platform to enable your end-to-end AI success—one that’s built on open standards and bolstered by a wide variety of ecosystem partner solutions.
Build Your Own AI Solution
For those seeking to build their own edge AI solutions from the ground up, consider our vendor-agnostic, edge-native software platform. This solution can help you build, deploy, and iterate AI workflows across your organization, with pro- and low-code development options and a catalog of production-ready solutions that can help kick-start your efforts. Designed to support the heterogeneous computing environments often found across the edge, this solution embraces open standards to help future-proof your AI efforts. It’s an ideal launching point for vertical-specific solutions.
Our platform also gives you the option to import your own existing application. Integrated telemetry dashboards can help you right-size hardware and optimize applications for the demands of edge environments.
Once you’re ready to deploy your software, our platform also makes it simpler to deploy, manage, and update your AI software across all your distributed edge environments. Cloud-like capabilities enable the agility and flexibility you need to scale and operate AI solutions at the edge of your infrastructure. Integrated security capabilities help you secure AI everywhere.
Watch our Intel Innovation session, “From Day-0 and Beyond: Intel’s New Platform for Managing Edge-Native Applications with Cloud-Like Agility” (sign-in or account registration required), to learn more about the platform and related development tools.
Purchase Ready-Made AI Solutions
Enterprise organizations looking to purchase AI solutions—including those looking to partner with a solution provider or system integrator—can rely on the Intel partner ecosystem for proven, interoperable AI capabilities. Our partner network is the world’s largest edge AI ecosystem, with hundreds of solutions spanning retail, industrial, healthcare, transportation, and more.
Our Intel® IoT Market Ready Solutions provide integrated hardware and software systems that are ready to help you solve your business problems.
Take a Combined Approach
Many organizations find that combining their own development efforts with prebuilt components can be the most efficient way to achieve AI success. Here, you can leverage a range of Intel resources that help you accelerate time to value and simplify development.
You can use the 30 AI reference kits we’ve created in partnership with Accenture, built on Intel® developer tools, to help streamline your efforts. These kits span both industries and use cases. You can even combine multiple kits to continue evolving your capabilities as your AI initiatives progress.
For example, the Demand Prediction, Predictive Maintenance, Product QA/QC, and Customer Support kits can be woven together to create an integrated solution for pharmaceutical life-cycle management, supporting use cases from forecasting demand to inspecting pills during production, maintaining equipment uptime, and deploying a chatbot to simplify robotics maintenance throughout production.
Additionally, you can take advantage of a wide range of other Intel® software resources that can be incorporated into your edge AI solutions, including:
- Intel® Distribution of OpenVINO™ toolkit, an open source toolkit for AI inference optimization that allows developers to write code once and deploy it anywhere across your heterogeneous environments.
- Intel® Edge Insights for Industrial, a free and open platform for machine vision and time series data.
- Edge AI Box for Video Analytics, a reference architecture that integrates video decode and analytic capabilities in a single box.
- Automated Self- Checkout Reference Implementation, which provides the critical components required to build and deploy self-checkout capabilities.
- Intel® IoT RFP Ready kits, which are commercially available kits built in collaboration with Intel partners to simplify AI-related IoT solutions.
Consider Your Potential Edge AI Challenges
Whether facing staffing issues in healthcare, looking to enhance productivity and profitability on the factory floor, seeking to streamline processes and prevent loss in retail stores, or tackling any number of other complex challenges, edge AI helps enterprises solve real-world problems.
But applying AI to address these problems also requires extending AI-enhanced capabilities to the edge of the network—the point where data is created and consumed, such as the plant floor, the hospital, or the storefront. Bringing AI capabilities to these environments presents new challenges when compared to running AI in the data center or the cloud, including:
- Adding AI to existing investments: Many edge environments feature legacy, fixed-function infrastructure with a variety of proprietary equipment and software. Space-constrained hardware needs to be able to support real-world requirements for accuracy and performance.
- Training and fine-tuning models: Edge AI models are unique and must be tuned for a specific industry or use-case dynamics. Human domain knowledge is often critical in these cases. For example, experienced weld inspectors can help AI understand how to detect good or bad welds. Enterprises need simple tools that help non‒data scientist experts transform their expertise into AI capabilities.
- Addressing hardware diversity: Edge-native applications will likely span a multitude of nodes, operating systems, connectivity protocols, compute and storage needs, energy and cost constraints, and compliance concerns. Developers need ways to deal with this complexity and support the distributed heterogeneous computing environment.
- Securing and managing distributed applications: Enterprises face new challenges as they seek to support advanced AI at the edge. Manageability is critical to applying AI at scale, and security is a necessity at every step along the way.
- Maximizing efficiency and reliability: Some edge environments place different kinds of stress on AI hardware, such as heat, moisture, or vibration. Edge AI solutions for use cases like traffic monitoring or quality assurance often need to be placed in areas with small amounts of physical real estate. Making it all happen with low power usage is also an important consideration for controlling costs and promoting sustainability.
Translate Domain Expertise into Data Science
Enterprises require new methods to bridge the gap between the knowledge of their specialists and their AI algorithms. They need ways to, for example, allow medical specialists to train AI models to recognize anomalies in medical scans or for QA teams to show AI models how to pinpoint manufacturing flaws. To that end, you can use the Intel® Geti™ platform, an easy-to-use tool that helps non‒data scientists more easily train AI models through labeling, annotation, and active learning. With this solution, data scientists, domain experts, developers, and AI professionals can all work together in the same platform, which makes applying computer vision AI to enterprise challenges fast and effective.
The Intel® Geti™ platform works with most AI frameworks and exports trained computer vision AI that can run on the devices you already have. REST APIs and the Intel® Geti™ software development kit (SDK) enable enterprises to integrate the platform into their value chain so they can push data directly into it and pull trained models directly into deployment pipelines.
Start Pursuing Your Edge AI Opportunity Today
As edge AI continues to bring together the physical and virtual worlds, Intel is committed to creating the unified, end-to-end fabric required to truly operationalize edge AI technologies.
Many of our customers are already seeing incredible results from their AI initiative. To find examples of how AI can help transform operations in your industry, browse our collection of customer success stories.
As you seek to harness the power of edge AI for your business, regardless of your adoption approach, Intel and our partner ecosystem are ready with solutions, technologies, and resources to help you simplify your initiative and accelerate time to value.